Research on the Application of Artificial Intelligence in Library Reader Behavior Analysis and Personalized Service
Xintong Li · 2024
This paper studies the application of artificial intelligence in library reader behavior analysis and personalized service. In order to deeply understand reader behavior and provide personalized service, this paper designs a service automation awareness model, which uses the nearest neighbor search K-means clustering algorithm. Firstly, this paper collects the data of library readers' borrowing records, browsing history, and searching behavior, and preprocesses and extracts the features of these data. Then, we input these features into the service automation perception model, and use the nearest neighbor search K-means clustering algorithm to classify and predict reader behavior. In order to verify the validity and performance of the model, a system simulation platform was constructed to simulate the changes of readers' behavior data under different scenarios, and the performance of the model under different data distributions was observed. Simulation results show that the model can accurately identify readers' reading preferences and provide personalized book recommendation service.